The following are the regression results of the determinants of performance in a virtual examination. dt 269.90 0.0000 Source Model 160.103587 Residual 273.23711 Total 433.7209 440.0756459 1.847 18438697 Number of a VE, 18421 Prob -aquared MH-red Root 1.346 234954658 0.363 .31520 Sed r. ti SOPA 2020 A2 Coot. SOPA2030 AI .2241917 COPA2020. AI .2217324 Male-.042006 Level 10000 1003858 con 1.641523 0361 0387336 .011134 0096285 0522696 9.20 5.72 -2.73 9.000 0.000 0.00 0.000 0.000 195) Cont. Intervall 1532712 2951123 1459562 .297708 -.0849241 -.0135972 0015019 1192097 1.339009 Variables Names: SGPA2020_A2: Grade Point Average (GPA)for last semester, i.e., when the online exams were written SGPA2020_AT: GPA for the semester preceding the online exams CGPA2020_AT: Cumulative GPA as at the semester preceding the online exams. You are required to answer the following questions, based on the results above: 1. How many observations were used for the regression? 2. How many parameters were estimated in this regression? 3. What is the Explained Sum of Squares (ESS) in the regression? 4. What is the Residual Sum of Squares (RSS) in the regression? 5. What is the Total Sum of Squares (TSS) from the regression? 6. How was the F-Statistic obtained? 7. Interpret the Adjusted R-Squared of the regression. 8. Test the Null Hypothesis that the regression line is not a good fit, against the alternative hypothesis that the line is a good fit. 9. Test the hypothesis that each of the parameters estimated is not statistically significant, against the alternative hypothesis that it is statistically significant 10. IF CGPA2020_Al increases by 1 point, by how much will SGPA2020_A2, increase on average? 11. Was there any difference in performance in the online exams between male and female students? If so, what is the difference? 12. What is the meaning of figure for"_cons" in this regression? The following are the regression results of the determinants of performance in a virtual examination. dt 269.90 0.0000 Source Model 160.103587 Residual 273.23711 Total 433.7209 440.0756459 1.847 18438697 Number of a VE, 18421 Prob -aquared MH-red Root 1.346 234954658 0.363 .31520 Sed r. ti SOPA 2020 A2 Coot. SOPA2030 AI .2241917 COPA2020. AI .2217324 Male-.042006 Level 10000 1003858 con 1.641523 0361 0387336 .011134 0096285 0522696 9.20 5.72 -2.73 9.000 0.000 0.00 0.000 0.000 195) Cont. Intervall 1532712 2951123 1459562 .297708 -.0849241 -.0135972 0015019 1192097 1.339009 Variables Names: SGPA2020_A2: Grade Point Average (GPA)for last semester, i.e., when the online exams were written SGPA2020_AT: GPA for the semester preceding the online exams CGPA2020_AT: Cumulative GPA as at the semester preceding the online exams. You are required to answer the following questions, based on the results above: 1. How many observations were used for the regression? 2. How many parameters were estimated in this regression? 3. What is the Explained Sum of Squares (ESS) in the regression? 4. What is the Residual Sum of Squares (RSS) in the regression? 5. What is the Total Sum of Squares (TSS) from the regression? 6. How was the F-Statistic obtained? 7. Interpret the Adjusted R-Squared of the regression. 8. Test the Null Hypothesis that the regression line is not a good fit, against the alternative hypothesis that the line is a good fit. 9. Test the hypothesis that each of the parameters estimated is not statistically significant, against the alternative hypothesis that it is statistically significant 10. IF CGPA2020_Al increases by 1 point, by how much will SGPA2020_A2, increase on average? 11. Was there any difference in performance in the online exams between male and female students? If so, what is the difference? 12. What is the meaning of figure for"_cons" in this regression